Designing and maintaining a software system's architecture typically involve making numerous design decisions, each potentially affecting the system's functional and nonfunctional properties. Understanding these design decisions can help inform future decisions and implementation choices, and can avoid introducing architectural inefficiencies later. Despite their importance, the support for engineers to make these decisions is generally lacking. There is a relative shortage of techniques, tools, and empirical studies pertaining to architectural design decisions. Moreover, design decisions are rarely well documented and are typically a lost artifact of the architecture creation and maintenance process. The loss of this information can thus hurt development. To address these shortcomings, we develop a set of techniques to enable methodical exploration of such decisions and their effects. We develop a technique, named RecovAr, for automatically recovering design decisions from the project's readily available history artifacts, such as an issue tracker and version control repository. Building on RecovAr, we create PredictAr that aims to prevent the consequences of inadvertent architectural change. The result of such changes is accumulation of technical debt and deterioration of software quality. In this dissertation we take a step toward addressing that scarcity by using the information in the issue and code repositories of open-source software systems to investigate the cause and frequency of such architectural design decisions. We develop a predictive model that is able to identify the architectural significance of newly submitted issues, thereby helping engineers to prevent the adverse effects of architectural decay. We close the loop by helping engineers to not only predict and recover architectural design decisions, but also make new design decisions that are informed and well-considered. To that end, we present eQual, a novel model-driven technique for simulation-based assessment of architectural designs that helps architects understand and explore the effects of their decisions.